Linear Mixed Models Random Effects
This feature requires the Advanced Statistics option.
Covariance type. This allows you to specify the covariance structure for the random-effects model. A separate covariance matrix is estimated for each random effect. The available structures are as follows:
- Ante-Dependence: First Order
- AR(1)
- AR(1): Heterogeneous
- ARMA(1,1)
- Compound Symmetry
- Compound Symmetry: Correlation Metric
- Compound Symmetry: Heterogeneous
- Diagonal
- Factor Analytic: First Order
- Factor Analytic: First Order, Heterogeneous
- Huynh-Feldt
- Scaled Identity
- Toeplitz
- Toeplitz: Heterogeneous
- Unstructured
- Unstructured: Correlation Metric
- Variance Components
See the topic Covariance Structures for more information.
Random Effects. There is no default model, so you must explicitly specify the random effects. Alternatively, you can build nested or non-nested terms. You can also choose to include an intercept term in the random-effects model.
You can specify multiple random-effects models. After building the first model, click Next to build the next model. Click Previous to scroll back through existing models. Each random-effect model is assumed to be independent of every other random-effect model; that is, separate covariance matrices will be computed for each. Terms specified in the same random-effect model can be correlated.
Subject Groupings. The variables listed are those that you selected as subject variables in the Select Subjects/Repeated Variables dialog box. Choose some or all of these in order to define the subjects for the random-effects model.